As pedestrian and bicyclist monitoring increases among public agencies, data quality principles must be included in data collection practices. This paper outlines key quality assurance principles and their application to pedestrian and bicyclist traffic count data. Three key principles of quality assurance are described: (a) quality assurance starts before data are collected, (b) acceptable quality is determined by the data's use, and (c) measures can quantify varying quality dimensions. Recommendations are made for two data quality measures: accuracy and validity.
The rapid expansion of transportation network companies (TNCs), such as Uber and Lyft, has led policy makers across the country to consider legislation to legalize and regulate TNC operations. In 2012, TNCs introduced a new travel option that used digital technology to provide an on-demand and highly automated private ride service, which has received support from consumers and investors. The emergence of TNCs has generated uncertainty about the legal status of TNC services, criticism from the taxicab industry, and concerns about public safety. In almost every U.S. state, policy makers have considered TNC legislation to address these issues, but there is no comprehensive source of information on the content of these policies. In this study, researchers systematically compiled a database of state TNC legislation and evaluated a set of policy issues addressed in the legislation. Thirty-four states and Washington, D.C., enacted legislation to authorize TNC operations through May 2016. These laws addressed policy areas including permits and fees, insurance and financial responsibility, driver and vehicle requirements, operational requirements, passenger protections, data reporting, and regulatory and rulemaking authority. This database can help policy makers navigate the evolving policy considerations presented by the rising popularity—and accompanying controversy—of TNCs. Key policy questions that emerged from this review of state TNC legislation include whether to regulate TNCs; if so, at what level of government; how to harmonize TNC policies with existing taxi and transportation policies; and how to address public safety without suppressing market competition.
Transportation performance measures based on travel time quantities satisfy a range of mobility purposes. The measures can show the effect of many transportation and land use solutions, and they are relatively easy to communicate to a range of audiences. The concept of total travel time has been discussed since the early 1950s, but because of data inaccessibility, the planning community has rarely used total travel time as a measure. For the initial implementation of the total peak period travel time measure in the Urban Mobility Report, data from the report's primary data sets were combined in a new way to estimate road users’ total travel time during the peak period. Data shortcomings were addressed with simplifying assumptions to create a calculation method that would offer a more refined value than would the use of raw or incomplete data. Total peak period travel time can provide additional explanatory power to a set of mobility performance measures and bridge the gap between traditional delay-based measurement and accessibility.
The performance-based planning and programming approach established by the Moving Ahead for Progress in the 21st Century Act (MAP-21) has necessitated the process of estimating congestion (delay) and reliability benefits from transportation system improvements. Agencies are experiencing a shift in policy focus from the average travel time to the reliability of travel time. By examining empirical data on before-and-after archived travel times at identified project locations to find evidence of observed reliability benefits, this paper addresses a gap in the literature about the overall role that reliability benefit estimations play in the decision-making process during transportation project prioritization, and the relative effects of different strategies on different reliability measures. In the process, the study investigated why and how the way the reliability measures are defined can affect their ability to capture the impacts (and benefits) of major system changes. Data for four different broad improvement categories and three different reliability performance measures (planning time index-95 [PTI95], planning time index-80 [PTI80], and level of travel time reliability [LOTTR]) revealed varying impacts of different strategies on different measures. PTI80 was better able to capture ground-level benefits experienced by most travelers and showed higher sensitivity to system improvements than PTI95. Another key finding was that LOTTR’s threshold-based definition limited its ability to capture observed reliability benefits accurately. The results provide a picture of magnitude and relative levels of observed benefits from different system improvements, which could help planners and practitioners better understand, anticipate, and incorporate the benefits expected from planned changes.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
customersupport@researchsolutions.com
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.